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Practical measures of integrated information for time-series data
journal contribution
posted on 2023-06-09, 00:40 authored by Adam BarrettAdam Barrett, Anil SethAnil SethA recent measure of ‘integrated information’, FDM, quantifies the extent to which a system generates more information than the sum of its parts as it transitions between states, possibly reflecting levels of consciousness generated by neural systems. However, FDM is defined only for discrete Markov systems, which are unusual in biology; as a result, FDM can rarely be measured in practice. Here, we describe two new measures, FE and FAR, that overcome these limitations and are easy to apply to time-series data. We use simulations to demonstrate the in-practice applicability of our measures, and to explore their properties. Our results provide new opportunities for examining information integration in real and model systems and carry implications for relations between integrated information, consciousness, and other neurocognitive processes. However, our findings pose challenges for theories that ascribe physical meaning to the measured quantities.
Funding
Towards a next-generation computational neuroscience; G0305; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL; EP/G007543/1
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Publication status
- Published
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- Published version
Journal
PLoS Computational BiologyISSN
1553-7358Publisher
Public Library of ScienceExternal DOI
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1Volume
7Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2016-03-30First Open Access (FOA) Date
2016-03-30First Compliant Deposit (FCD) Date
2016-03-29Usage metrics
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